Taxonomy for integrating scheduling theory and human factors: Review and research opportunities

摘要

Consider a human facing a variety of physically or cognitively demanding tasks, who then performs these tasks in a sequence that has been determined either strategically or arbitrarily. Just as the exhaustive scheduling literature has repeatedly demonstrated the significant impact that scheduling decisions have on system performance, the human factors literature suggests that task sequencing decisions have a profound impact on human performance and well-being. The latter claim is justified almost exclusively by empirical methods. The alternative of applying classic scheduling theory to sequencing decisions involving human tasks was proposed over a decade ago. However, these pioneering frameworks did not delineate a mathematical basis for incorporating human behavior into the machine scheduling paradigm. The purpose of this paper is to establish a framework for scheduling human tasks that account for physical and/or cognitive human characteristics and behaviors. The framework is constructed by surveying the human factors literature in an effort to identify human characteristics that are relevant to task sequencing, and by reviewing emerging areas of the scheduling literature that are auspicious with respect to modeling these human characteristics in a scheduling context. Interdisciplinary research opportunities in scheduling and human factors are also discussed. Relevance to industry: This paper is inspired by the physical and cognitive challenges associated with semi-automated order picking in warehouses. While pick schedules are often designed in practice based on metrics such as maximizing throughput and meeting delivery schedules, this paper describes a framework for task sequencing that accounts for the worker's risk and aims to maximize the worker's productivity. The proposed task-sequencing framework is general and relevant to any working environment characterized by demanding tasks, task variety, and objectives related to productivity and safety.